Cell cycle modelling |
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| Authors: | L Alberghina L Mariani E Martegani |
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| Affiliation: | 1. Dipartimento di Fisiologia e Biochimica Generali, Sezione di Biochimica Comparata, Università di Milano, Via Celoria 26, 20133 Milano, Italy;2. Istituto di Dinamica dei Sistemi e di Bioingegneria, CNR and Istituto di Elettronica ed Elettrotecnica, Università di Padova, 35100 Padova, Italy;1. Department of Physiology, Lagos State University College of Medicine, Lagos State, Ikeja 23401, Nigeria;2. Laboratory for Reproductive Physiology and Developmental Programming, Department of Physiology, University of Ibadan, Ibadan 23402, Nigeria;1. State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;2. Department of Chemistry, School of Sciences, Zhejiang Sci-Tech University, Hangzhou 310018, China;3. Environment Research Institute, Shandong University, Jinan 250100, China;4. Institute of Environment and Health, Jianghan University, Wuhan 430056, China;5. University of Chinese Academy of Sciences, Beijing 100049, China;1. Department of Physics, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran;2. Department of petroleum engineering, School of chemical and petroleum engineering, Shiraz University, Iran;3. Physics department, Sharif University of Technology, P.O. Box 11155-9161, Tehran, Iran |
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| Abstract: | Models able to describe the events of cellular growth and division and the dynamics of cell populations are useful for the understanding of functional control mechanisms and for the theoretical support for automated analysis of flow cytometric data and of cell volume distributions. This paper reports on models that we have developed with this aim for different kinds of cells. The models are composed by two subsystems: one describes the growth dynamics of RNA and protein, and the second accounts for DNA replication and cell division, and describe in a rather unitary frame the cell cycle of eukaryotic cells, like mammalian cells and yeast, and of prokaryotic cells. The model is also used to study the effects of various sources of variability on the statistical properties of cell populations, and we find that in microbial cells the main source of variability appears to be an inaccuracy of the molecular mechanism that monitors cell size. In normal mammalian cells another source of variability, that depends upon the interaction with growth factors which give competence, is apparent. An extended version of the model, which comprises also this additional variability, is presented and used to describe the properties of mammalian cell growth. |
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